{"id":"W6889206159","doi":"10.25549/chs-m10224","title":"Real estate promotion handbill from the W. M. Garland Company predicting Los Angeles population growth for 1920, 1911","year":2012,"lang":"en","type":"dataset","venue":"University of Southern California Digital Library","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Real estate; Promotion (chess); Sign (mathematics); Population; GRASP; Quarter (Canadian coin)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007904582,0.002762589,0.001192316,0.004012793,0.0009063256,0.002169274,0.002231188,0.0017826,0.0875261],"category_scores_gemma":[0.003621317,0.0007764968,0.001315131,0.004787409,0.0002849314,0.001688993,0.001990551,0.001868651,0.1722613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001767689,"about_ca_system_score_gemma":0.00184125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09120324,"about_ca_topic_score_gemma":0.1992849,"domain_scores_codex":[0.9992461,0.0001015973,0.00005727799,0.000228741,0.0002518494,0.0001145001],"domain_scores_gemma":[0.9980533,0.0002749848,0.0001390176,0.0004537959,0.0008011185,0.0002778481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003414451,0.00003035457,0.001609953,0.0001304652,0.00001606122,0.00001513799,0.000007809702,0.0002244281,0.00004449875,0.00006300702,0.9945102,0.003313938],"study_design_scores_gemma":[0.0002813193,0.00006502262,0.02498879,0.0003648066,0.00004474398,0.0001003133,0.0001990414,0.002829967,0.0005933245,0.0004626846,0.9700096,0.00006044134],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004943865,0.000118949,0.00007914092,0.00009901554,0.00007389926,0.00001270886,0.9969227,0.0007245393,0.001474645],"genre_scores_gemma":[0.000493291,0.00003762044,0.0001583431,0.00002185061,0.00001171476,0.00002319659,0.997626,0.00003889977,0.001589191],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09120324,"threshold_uncertainty_score":0.2928039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01319836416878119,"score_gpt":0.1829443862444261,"score_spread":0.1697460220756449,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}